• Create data-driven applications to publish analytical findings
• Visualize interactive bar charts, scatterplots, maps and images
• Engage users through drop down menus and search inputs
• Communicating to data sources using the Google Sheets API
• Customize and style applications using Cascading Style Sheets (CSS)
• In this RShiny tutorial, you'll gain training as we cover topics including R code, R script, Shiny server. These skills are applicable for data science, machine learning, working with open source code and working in github with datasets. Additional tangential skills include docker, docerize, tidyverse, shinymatrix, matrix inputs and more!

This course is meant to teach the basics of building an app using RShiny. It presents a general introduction to the capabilities of RShiny with a particular focus on "learning by doing." At the end of each week of instruction, you'll complete a "wrap-up exercise" and quiz that reinforce the techniques you've learned.

Week 1

• Getting Set Up
• Using R Studio IDE for Shiny
• Basic UI
• Client Side vs Server Side Components

Week 2

• Server Side UI
• Leaflet Maps
• Server Side Outputs
• Buttons, Modal Viewers and Observe Events

Week 3

• Working with Data
• The Reactive and Browser Functions
• Customizing Your App with consideration of CSS Rules and Custom Skins
• Deploying Your Application!

Week 4

• Setting Things Up - Where to Begin
• Starting a New Project
• Filters for Interactivity
• Maps and Journals
• Final Projects!